Ruby: Productive Programming Language
Every few years something significant happens in the land of computer programming. In my opinion the Ruby computer language is such a landmark.
Over the years I have seen programmer productivity go up. These are no hard measured calculations, but I have the impression that every five years the speed of delivering software doubles. Not only that, the curve for writing maintainable software appears to increase linearly too. A lot of that speed can be attributed to the tools of a developer, and core to these tools is the computer language.
Computer languages are essentially alike. There are more similarities than differences between any language. Nevertheless, the differences have a large impact on solving problems, finding ways of expression and human interaction. For example, LISP, a language of great beauty and simplicity in conception, reflects its allegiance more to computers than to humans. A language easy to interpret is not necessarily easy to program, as many a student can attest. LISP's most amazing feature is that it shows with how few rules one can create a powerful computer language.
Structured languages like Pascal and C clearly bridged a gap between native assembler and quick, human-readable coding. C is still widely used where performance matters--it is possible to write close to the assembler, as the Linux and BSD kernels prove.
With C++ in the early nineties, I personally went through a period of exploration and discovery. Classes, objects, containers, operator overloading, the works. Reading Stroustrup's classic book was crucial to understanding C++ as a language, and I loved it. But with hindsight I can see it takes something extra to become productive in C++; it is not for everyone.
Java came to the rescue. A much simpler language with an elegance in OOP (object-oriented programming), Java does have some down sides, like slow JVMs dealing with large libraries. The language itself has some short comings too. Many experienced C++ programmers use Java, and the complaint will come that it feels like working with their hands tied behind the back. Nevertheless Java is great for corporate-type team programming efforts. As a language it goes some way in enforcing structure and using OOP concepts.
In parallel, two other languages made a mark in the nineties: Perl and Python. Both are (interpreted) scripting languages and have some real advantages over C++ and Java in terms of delivery time of software (more on that below). With current levels of computing power, performance is hardly an issue for most "user-land" software.
Perl was a revolution in a way. and most of its productivity boost was due to the introduction of a full programming language with light notation for regular expressions, arrays and especially hashes.
Perl has some real problems, though, as almost everyone will assert who has participated in large Perl programming efforts. Perl has OOP extensions, but they are non-obvious and laborious. I did enjoy learning Perl OOP because it taught me a lot about OOP itself and how to implement OOP in a language as a single hack. Writing Perl OOP, however, is no joy. Maintaining a large Perl source base is only possible with the highest level of discipline by the coders, and the language itself does not help enforcing correct coding practices.
Python is cleaner as a language though its OOP was added as an afterthought--and it shows. I spent some serious time looking into Python and did not like it that much. It gives a lot but runs short, for example, with object elements all being public. In a team effort, that means developers have trouble understanding how their classes are being used (or abused). In this situation, I would even have trouble trusting my own code. Operator overloading is ugly, the syntax of a colon after an if statement I find to be non-obvious, etc. The indentation idea is clever, but somehow it doesn't improve code readability. In short, Python almost makes it but not quite.
Late last year I got my hands on the Ruby book by the (self-named) pragmatic programmers, Dave Thomas and Andy Hunt. The book also has an on-line version. I read the book in one go, and it goes into the hall of fame of important computer books, as far as I am concerned, right next to the Stroustrup. After reading it, I almost skipped sleep for a week because I was so excited by the implications of Ruby, a programming language that reads like poetry.
The author of Ruby, Yukihiro Matsumoto, aka Matz, knows his languages (LISP, Small Talk, Perl, Python and others) and aimed to create his perfect language. Ruby follows the Principle of Least Surprise and, funny enough, gets close. It feels, in fact, exactly like the computer language I have wanted to design all my life (without really knowing it).
Ruby was developed after 1994 and does not carry the baggage of Perl and Python; it is the new kid on the block. It comes with extensive libraries, not as rich as Perl's CPAN, but after a year of working with Ruby, I haven't missed any critical components. Ruby is complete with HTML and FTP classes, CGI support, XML parsers, database libraries, GTK and Qt bindings and even a pure Ruby BTree library. It is also quite straightforward to link up Ruby and Python libraries, which gives it an even richer base. Ruby is well supported on UNIX and Windows; developing on UNIX and deploying on Windows works without a hitch, including GUI development.
Fast/Flexible Linux OS Recovery
On Demand Now
In this live one-hour webinar, learn how to enhance your existing backup strategies for complete disaster recovery preparedness using Storix System Backup Administrator (SBAdmin), a highly flexible full-system recovery solution for UNIX and Linux systems.
Join Linux Journal's Shawn Powers and David Huffman, President/CEO, Storix, Inc.
Free to Linux Journal readers.Register Now!
|Working with Command Arguments||May 28, 2016|
|Secure Desktops with Qubes: Installation||May 28, 2016|
|CentOS 6.8 Released||May 27, 2016|
|Secure Desktops with Qubes: Introduction||May 27, 2016|
|Chris Birchall's Re-Engineering Legacy Software (Manning Publications)||May 26, 2016|
|ServersCheck's Thermal Imaging Camera Sensor||May 25, 2016|
- Tips for Optimizing Linux Memory Usage
- Working with Command Arguments
- Secure Desktops with Qubes: Introduction
- Secure Desktops with Qubes: Installation
- Download "Linux Management with Red Hat Satellite: Measuring Business Impact and ROI"
- CentOS 6.8 Released
- The Italian Army Switches to LibreOffice
- Linux Mint 18
- Oracle vs. Google: Round 2
- Chris Birchall's Re-Engineering Legacy Software (Manning Publications)
Until recently, IBM’s Power Platform was looked upon as being the system that hosted IBM’s flavor of UNIX and proprietary operating system called IBM i. These servers often are found in medium-size businesses running ERP, CRM and financials for on-premise customers. By enabling the Power platform to run the Linux OS, IBM now has positioned Power to be the platform of choice for those already running Linux that are facing scalability issues, especially customers looking at analytics, big data or cloud computing.
￼Running Linux on IBM’s Power hardware offers some obvious benefits, including improved processing speed and memory bandwidth, inherent security, and simpler deployment and management. But if you look beyond the impressive architecture, you’ll also find an open ecosystem that has given rise to a strong, innovative community, as well as an inventory of system and network management applications that really help leverage the benefits offered by running Linux on Power.Get the Guide